Physiologic responses to water immersion in man: A compendium of research

A total of 221 reports published through December 1973 in the area of physiologic responses to water immersion in man were summarized. The author's abstract or summary was used whenever possible. Otherwise, a detailed annotation was provided under the subheadings: (1) purpose, (2) procedures and methods, (3) results, and (4) conclusions. The annotations are in alphabetical order by first author; author and subject indexes are included. Additional references are provided in the selected bibliography

Insulin-like growth factor-I ameliorates demyelination induced by tumor necrosis factor-α in transgenic mice

Our laboratories have reported that TNF-α causes myelin damage and apoptosis of oligodendrocytes and their precursors in vitro and in vivo. We also have reported that IGF-I can protect cultured oligodendrocytes and their precursors from TNF-α-induced damage. In this study, we investigated whether IGF-I can protect oligodendrocytes and myelination from TNF-α-induced damage in vivo by cross-breeding TNF-α transgenic (Tg) mice with IGF-I Tg mice that overexpress IGF-I exclusively in brain. At 8 weeks of age, compared to wildtype (WT) mice, the brain weights of TNF-α Tg mice were decreased by ~20%, while those of IGF-I Tg mice were increased by ~20%. The brain weights of mice that carry both TNF-α and IGF-I transgenes (TNF-α/IGF-I Tg mice) did not differ from WT mice. As judged by histochemical staining and immunostaining, myelin content in the cerebellum of TNF-α/IGF-I Tg mice was similar to that in WT mice and much more than that in TNF-α Tg mice. Consistently, western immunoblot analysis showed that myelin basic protein abundance in the cerebellum of TNF-α/IGF-I Tg mice was double that in TNF-α Tg mice. Compared to WT mice, the number of oligodendrocytes was decreased by ~36% in TNF-α Tg mice, while it was increased in IGF-I Tg mice by ~40%. Oligodendrocyte number in TNF-α/IGF-I Tg mice was almost as twice many as that in TNF-α Tg mice. Furthermore, IGF-I overexpression significantly reduced TNF-α-induced increases in apoptotic cell number, active caspase-3 abundance and degraded MBP. Our results indicate that IGF-I is capable of protecting myelin and oligodendrocytes from TNF-α-induced damage in vivo

Deep neural network augmentation: generating faces for affect analysis

This paper presents a novel approach for synthesizing facial affect; either in terms of the six basic expressions (i.e., anger, disgust, fear, joy, sadness and surprise), or in terms of valence (i.e., how positive or negative is an emotion) and arousal (i.e., power of the emotion activation). The proposed approach accepts the following inputs:(i) a neutral 2D image of a person; (ii) a basic facial expression or a pair of valence-arousal (VA) emotional state descriptors to be generated, or a path of affect in the 2D VA space to be generated as an image sequence. In order to synthesize affect in terms of VA, for this person, 600,000 frames from the 4DFAB database were annotated. The affect synthesis is implemented by fitting a 3D Morphable Model on the neutral image, then deforming the reconstructed face and adding the inputted affect, and blending the new face with the given affect into the original image. Qualitative experiments illustrate the generation of realistic images, when the neutral image is sampled from fifteen well known lab-controlled or in-the-wild databases, including Aff-Wild, AffectNet, RAF-DB; comparisons with generative adversarial networks (GANs) show the higher quality achieved by the proposed approach. Then, quantitative experiments are conducted, in which the synthesized images are used for data augmentation in training deep neural networks to perform affect recognition over all databases; greatly improved performances are achieved when compared with state-of-the-art methods, as well as with GAN-based data augmentation, in all cases

Recognition of affect in the wild using deep neural networks

In this paper we utilize the first large-scale "in-the-wild" (Aff-Wild) database, which is annotated in terms of the valence-arousal dimensions, to train and test an end-to-end deep neural architecture for the estimation of continuous emotion dimensions based on visual cues. The proposed architecture is based on jointly training convolutional (CNN) and recurrent neural network (RNN) layers, thus exploiting both the invariant properties of convolutional features, while also modelling temporal dynamics that arise in human behaviour via the recurrent layers. Various pre-trained networks are used as starting structures which are subsequently appropriately fine-tuned to the Aff-Wild database. Obtained results show premise for the utilization of deep architectures for the visual analysis of human behaviour in terms of continuous emotion dimensions and analysis of different types of affect

Morphological differences in Parkinson's disease with and without rest tremor

Background : Rest tremor is a hallmark of Parkinson's disease (PD), but its pathogenesis remains incompletely understood. Nigro-striatal dopamine deficiency correlates best with bradykinesia, but not with tremor. Oscillating neurons in one or multiple localizations within the basal gangliathalamo-cortical loop may cause rest tremor, and an active contribution of the cerebellum and the cerebello-thalamo-cortical projections has been postulated. Objective : To compare the pattern of grey matter volume in PD patients with and without tremor to identify structural correlates of rest tremor. Methods : Voxel-based morphometry (VBM) of a high-resolution 3 Tesla, T1-weighted MR images, pre-processed according to an optimized protocol using SPM2, was performed in 24 patients with mild to moderate PD comparing local grey matter volume in patients with (n = 14) and without rest tremor (n = 10). Results : Grey matter volume is decreased in the right quadrangular lobe and declive of the cerebellum in PD with tremor compared to those without (PFDR < 0.05). Conclusions : These results demonstrate for the first time morphological changes in the cerebellum in PD patients with rest tremor and highlight the involvement of the cerebellum and cerebello- thalamo-cortical circuit in the pathogenesis of parkinsonian rest tremo

Aff-Wild: Valence and Arousal ‘in-the-wild’ Challenge

The Affect-in-the-Wild (Aff-Wild) Challenge proposes a new comprehensive benchmark for assessing the performance of facial affect/behaviour analysis/understanding 'in-the-wild'. The Aff-wild benchmark contains about 300 videos (over 2,000 minutes of data) annotated with regards to valence and arousal, all captured 'in-the-wild' (the main source being Youtube videos). The paper presents the database description, the experimental set up, the baseline method used for the Challenge and finally the summary of the performance of the different methods submitted to the Affect-in-the-Wild Challenge for Valence and Arousal estimation. The challenge demonstrates that meticulously designed deep neural networks can achieve very good performance when trained with in-the-wild data